DESCRIPTION (Applicant's Abstract): We live in an uncertain world where the consequences of our actions are not always predictable. Therefore, the decisions to invest in the stock market, to undergo a medical treatment, or to go to court depend on our assessment of the chances that the market will go up, the treatment will be successful, or the court will decide in our favor. Because in general we do not have objective methods for computing the probabilities of such events, we must rely on human judgment as the major instrument for assessing uncertainty. Hence, the question of how people evaluate evidence and assess uncertainty is highly relevant to many aspects of our lives, from the diagnosis of a patient to the evaluation of expert judgment. An extensive body of research on judgment under uncertainty indicates that intuitive judgments of both lay people and experts are often at variance with accepted normative principles of probability and statistics. These findings have commonly been attributed to cognitive limitations and explained in terms of judgmental heuristics or simplifying strategies. This proposal presents a new approach to subjective probability based on the notion of evidential support. It gives rise to a formal representation that is compatible with heuristic process-based accounts and encompasses a wide range of phenomena within a unified theoretical framework. The application consists of four parts. The first part presents a new theory of belief in which the judged probability of an event depends on the specificity of its description. According to this account, judged probability is increased by unpacking the focal hypothesis and decreased by unpacking the alternative hypothesis. Part 2 describes a series of experiments designed to test this model in several settings, including medical diagnosis and lay perceptions of causes of death. Part 3 extends the theory to the analysis of conditional probability and evidential support, and it addresses the relation between contingency and causality judgments. Part 4 deals with ambiguity or vagueness and provides a method for assessing the imprecision of belief in terms of upper and lower probability judgments. It is hoped that a better understanding of our cognitive limitations could help improve the quality of human judgments.